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Depression is among the most common neuropsychiatric disorders. It remains unclear whether brain abnormalities associated with depression reflect the pathological state of the disease or neurobiological traits predisposing individuals to depression. Parental history of depression is a risk factor that more than triples the risk of depression. We compared white matter (WM) microstructure cross-sectionally in 40 children ages 8-14 with versus without parental history of depression (At-Risk vs. Control). There were significant differences in age-related changes of fractional anisotropy (FA) between the groups, localized in the anterior fronto-limbic WM pathways, including the anterior cingulum and the genu of the corpus callosum. Control children exhibited typical increasing FA with age, whereas At-Risk children exhibited atypical decreasing FA with age in these fronto-limbic regions. Furthermore, dorsal cingulate FA significantly correlated with depressive symptoms for At-Risk children. The results suggest maturational WM microstructure differences in mood-regulatory neurocircuitry that may contribute to neurodevelopmental risk for depression. The study provides new insights into neurodevelopmental susceptibility to depression and related disabilities that may promote early preventive intervention approaches.

Despite growing evidence for atypical amygdala function and structure in major depression, it remains uncertain as to whether these brain differences reflect the clinical state of depression or neurobiological traits that predispose individuals to major depression. We examined function and structure of the amygdala and associated areas in a group of unaffected children of depressed parents (at-risk group) and a group of children of parents without a history of major depression (control group). Compared to the control group, the at-risk group showed increased activation to fearful relative to neutral facial expressions in the amygdala and multiple cortical regions, and decreased activation to happy relative to neutral facial expressions in the anterior cingulate cortex and supramarginal gyrus. At-risk children also exhibited reduced amygdala volume. The extensive hyperactivation to negative facial expressions and hypoactivation to positive facial expressions in at-risk children are consistent with behavioral evidence that risk for major depression involves a bias to attend to negative information. These functional and structural brain differences between at-risk children and controls suggest that there are trait neurobiological underpinnings of risk for major depression., Highlights • We studied brain correlates of familial risk for major depression. • At-risk children exhibited hyperactivation to fearful faces compared to controls. • At-risk children exhibited hypoactivation to happy faces compared to controls. • At-risk children exhibited reduced amygdala volume compared to controls. • These results identify trait neurobiological underpinnings of risk for depression.

Context: Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. Objective: To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Design: Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Setting: Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Patients: Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Interventions: Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Main Outcome Measures: Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Results: Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. Conclusions: The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized medicine approaches for optimally selecting among treatment options for a patient.